摘要
基于最小期望损失的角度建立最优定价模型,并引入粒子群算法予以求解。结合具体算例,根据不同库存量s及库存量s和折扣价φ的不同组合,分别获得达到最小期望损失cs(ω*)的最优定价ω*。对仿真结果的分析表明:粒子群算法获得的结果能很好地解释所建模型及经济现实,并为季节性商品的销售商制定最优销售价格和折扣价格提供决策依据。
Considering minimized the seller＇s total expected loss, the paper proposes optimal pricing model that is solved by Particle Swarm Optimization （PSO）. With a numerical example, minimized expected loss and optimal price can be drawn under two situations including different stocks and different combination of stocks and discount price. The analysis indicates that the result with PSO is rational. Furthermore, the suggestions for the sellers to determine the optimal price are also given.
出处
《系统工程理论方法应用》
北大核心
2005年第4期326-329,共4页
Systems Engineering Theory·Methodology·Applications
关键词
季节性商品
最优定价
粒子群算法
期望损失
seasonal commodities
optimal pricing
particle swarm optimization
expectation loss
